The goal of this paper is to estimate the mass and auxiliary power of a vehicle simultaneously. Auxiliary power is the portion of the load power that is consumed by any auxiliary devices such as A/C compressor which is connected to the engine directly. This estimation has many potential applications especially in power management control systems of hybrid and plug-in-hybrid vehicles to improve their efficiency.

The parameter estimation algorithm is based on power balance of the vehicle. That is, total generated power by the engine should be equal to the power required for moving the vehicle plus the power consumed by the auxiliary devices. After developing the system model, Kalman filter is applied for the estimation of the auxiliary power and vehicle mass.

The proposed estimation algorithm uses the signals available through the vehicle control area network (CAN), and no extra sensor is required. It is assumed that the road grade is provided by a Global Positioning System (GPS) installed in the car. Simulations are presented to show the performance of the estimation algorithm in both city and highway driving cycles. The estimated and actual results are in very good agreement.

This content is only available via PDF.
You do not currently have access to this content.